Instructions to use lsmpp/kontextrefiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsmpp/kontextrefiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsmpp/kontextrefiner", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| name: "\U0001F31F Remote VAE" | |
| description: Feedback for remote VAE pilot | |
| labels: [ "Remote VAE" ] | |
| body: | |
| - type: textarea | |
| id: positive | |
| validations: | |
| required: true | |
| attributes: | |
| label: Did you like the remote VAE solution? | |
| description: | | |
| If you liked it, we would appreciate it if you could elaborate what you liked. | |
| - type: textarea | |
| id: feedback | |
| validations: | |
| required: true | |
| attributes: | |
| label: What can be improved about the current solution? | |
| description: | | |
| Let us know the things you would like to see improved. Note that we will work optimizing the solution once the pilot is over and we have usage. | |
| - type: textarea | |
| id: others | |
| validations: | |
| required: true | |
| attributes: | |
| label: What other VAEs you would like to see if the pilot goes well? | |
| description: | | |
| Provide a list of the VAEs you would like to see in the future if the pilot goes well. | |
| - type: textarea | |
| id: additional-info | |
| attributes: | |
| label: Notify the members of the team | |
| description: | | |
| Tag the following folks when submitting this feedback: @hlky @sayakpaul | |